報告題目：Crowdsourcing science for environmental and societal decision making

主講人：Kumaraswamy Ponnambalam, Professor, Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada

時間地點：2017年6月29日10:00-11:30 將軍路校區(qū)經(jīng)管院704室

報告摘要：Crowdsourcing is defined as a method for obtaining information using the services of a large number of people, either paid or unpaid, typically via the Internet. A citizen is an inhabitant of a city or town entitled to the rights and privileges and often is involved in the decision making especially relating to society and environment. Science is a systematized knowledge and science based decision making can be synonymous to informed decision making.Citizens have been doing science for thousands of years and that is our foundation for knowledge so what is new? The ability to do it quick and easily spread the knowledge worldwide instantly is new! Doing science using personal observations but collected through devices (smartphones, websites), inexpensive devices for collection of data such cameras, GPS, weather stations, and others. Getting a citizen to do science as a hobby or voluntarily with some incentives, such as points in a game, is becoming popular (Geocaching is one recent such activity). Also, local and global issues of what-if scenarios can entice everyone to contribute. Why is this important? Informed citizen can help with more sensible decision making. Those who contribute even in a small way tends to be more interested in the decision making process. We need to make science easily viable but, like arts, the entertainment requirements of science, which reach most audience, require a large amount of resources. But today, easily available devices and the ability to transmit and store a large amount of information more or less freely have made it crowdsourcing science feasible. Governments who traditionally support general science are often cutting funds due to their political points of view and so we have to crowd source to get scientific work to continue in dire circumstances. There are endless possibilities for citizen science projects and it is good to find issues locally relevant but can also be globally understood to make up the objectives of such projects..

報告人簡介：EducationBE – Madras (1979); MSc – National University of Ireland (1981); PhD - University of Toronto (1987)Research Interests:Design Optimization under Uncertainty:Development of new methodologies for design optimization under uncertainty explicitly considering risk and applying the newly developed techniques in engineering including civil, chemical, electrical and environmental engineering problems are some of our main objectives. Because of the interdisciplinary nature of the many applications, much of the work has been done in collaboration with colleagues from both inside and outside the university.  In addition, I am also working in the Application of Intelligent Systems, to hydrology and water resources, decision making in health, control of satellite communications, and fault detection analysis.Selected Publications in Refereed Journals:?Narayan A, Ponnambalam K. Risk-averse stochastic programming approach for microgrid planning under uncertainty [J]. Renewable Energy, 2017, 101:399-408.?Eajal A A, Shaaban M F, Ponnambalam K, et al. Stochastic Centralized Dispatch Scheme for AC/DC Hybrid Smart Distribution Systems[J]. IEEE Transactions on Sustainable Energy, 2016, 7(3):1046-1059.?Eajal A A, Abdelwahed M A, El-Saadany E F, et al. A Unified Approach to the Power Flow Analysis of AC/DC Hybrid Microgrids[J]. IEEE Transactions on Sustainable Energy, 2016, 7(3):1145-1158.?Mousavi S J, Alizadeh H, Ponnambalam K. Storage-yield analysis of surface water reservoirs: the role of reliability constraints and operating policies [J]. Stochastic Environmental Research and Risk Assessment, 2014, 28(8):2051-2061.?López J á, Ponnambalam K. Long-term uncertainty evaluation of pool electricity markets[J]. Energy Policy, 2010, 38(2):840-849.

舉辦單位：南航經(jīng)管學(xué)院智能決策與風(fēng)險分析研究所